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{
"name": "2dplanes",
"n_num_features": 10,
"n_cat_features": 0,
"train_size": 26091,
"val_size": 6523,
"test_size": 8154,
"source": "https://www.openml.org/search?type=data&status=active&id=215&sort=runs",
"task_intro": "**Author**: \n**Source**: Unknown - \n**Please cite**: \n\nThis is an artificial data set described in Breiman et al. (1984,p.238) \n (with variance 1 instead of 2). \n \n Generate the values of the 10 attributes independently\n using the following probabilities:\n\n P(X_1 = -1) = P(X_1 = 1) = 1/2\n P(X_m = -1) = P(X_m = 0) = P(X_m = 1) = 1/3, m=2,...,10\n\n Obtain the value of the target variable Y using the rule:\n\n if X_1 = 1 set Y = 3 + 3X_2 + 2X_3 + X_4 + sigma(0,1)\n if X_1 = -1 set Y = -3 + 3X_5 + 2X_6 + X_7 + sigma(0,1)\n\n Characteristics: 40768 cases, 11 continuous attributes\n Source: collection of regression datasets by Luis Torgo (ltorgo@ncc.up.pt) at\n http://www.ncc.up.pt/~ltorgo/Regression/DataSets.html\n Original source: Breiman et al. (1984, p.238).",
"task_type": "regression",
"openml_id": 215,
"n_classes": 1,
"num_feature_intro": {
"x1": "x1",
"x2": "x2",
"x3": "x3",
"x4": "x4",
"x5": "x5",
"x6": "x6",
"x7": "x7",
"x8": "x8",
"x9": "x9",
"x10": "x10"
},
"cat_feature_intro": {}
} |